Update app.py

app.py

@@ -15,15 +15,15 @@ nlp_a = pipeline('question-answering', model='mrm8488/distill-bert-base-spanish-
     ))
 def generate_summary(text):
    inputs = tokenizer([text], padding="max_length", truncation=True, max_length=64, return_tensors="pt")
-   input_ids = inputs.input_ids.to(device)
-   attention_mask = inputs.attention_mask.to(device)
+   input_ids = inputs.input_ids
+   attention_mask = inputs.attention_mask
    output = model.generate(input_ids, attention_mask=attention_mask)
    return tokenizer.decode(output[0], skip_special_tokens=True)
 def generate_simple_text(data):
     outputs = []
     for text in data.split("."):
         inputs = tokenizer_s(text, max_length=1024, padding=True, truncation=True, return_tensors='pt')
-        output = model_s.generate(inputs['input_ids'].to(device), max_length=100)
+        output = model_s.generate(inputs['input_ids'], max_length=100)
         outputs.append(['\n'.join([tokenizer_s.decode(g, skip_special_tokens=True, clean_up_tokenization_spaces=False) for g in output])])
     return outputs
 def generate_questions(data):